Valerie Capers Workman, CHRO at Empower Pharmacy

Show Notes

The Human Last Mile: Empower Pharmacy’s CHRO on AI Fluency, Ethics, and HR Transformation

Summary

AI in HR isn’t about replacing people—it’s about redefining excellence and freeing humans to do higher-order work.

Valerie Capers Workman, Chief Human Resources Officer at Empower Pharmacy and author of two books on AI, shares how she’s leading company-wide AI transformation while rebuilding the HR tech stack with human-in-the-loop design.

Valerie tackles the real blockers—fear, security, ethics, IP, and inequity—and explains why “excellence now requires AI” and how leaders can communicate that without triggering defensiveness. She breaks down a practical operating model: use AI for task work, keep humans as the “last mile” decision-makers, and build AI fluency through structured, role-based training so no one is left behind.

Expect candid stories, from coaching a team member past “AI is cheating” to using saved time for strategic thinking, plus how to set guardrails for sensitive areas like employee relations.

Timestamps

[00:45] – Guest intro: CHRO role at Empower Pharmacy and leading AI across HR and the business

[02:16] – The real challenges: fear of replacement, ethics, security, and IP concerns

[03:24] – Redefining excellence and leveling the field: reluctance, inequity, and access

[06:16] – Coaching in practice: moving from “AI is cheating” to standout work—and time back

[08:42] – What leaders must do: shift routine to AI to create space for strategic thinking

[10:24] – Managing risk: automation misfires, ER sensitivity, and designing for control

[11:48] – Design principle: human-in-the-loop “last mile” for all critical HR decisions

[15:45] – Building AI fluency: pilot curriculum, company-wide training, and starting before perfect

Takeaways

- Design AI with humans as the last mile—keep judgment, empathy, and final decisions with leaders.

- Build AI fluency by role; launch a pilot curriculum and scale it so no one is left behind.

- Reframe AI as a performance multiplier: use it for tasks to create room for strategy and EQ work.

- Set clear guardrails (ethics, security, IP) and choose platforms that preserve human control.

- Start now with small experiments; momentum beats perfection in a fast-changing tech landscape.

- Normalize failure and iteration—use “bad” outputs to sharpen prompts, thinking, and processes.

Sponsor

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See a demo at ⁠⁠⁠⁠https://www.allvoices.co/

What is HR Voices?

HR Voices is a scenario-based podcast for People Leaders who’ve actually had to make the call.

Each episode brings experienced HR and People leaders into realistic, anonymized workplace scenarios—the kind you recognize immediately. Performance issues. Messy conflicts. Investigations that don’t fit neatly into a policy box. Instead of talking about their own companies, guests react to outside cases and walk through how they’d think it through in real time.

There are no right answers here. What you’ll hear is judgment: how seasoned leaders balance risk, fairness, legal reality, and humanity when the stakes are high and the path isn’t obvious.

HR Voices is for HR, People Ops, legal, and leaders who want to hear how other smart humans actually handle employee relations—without confidentiality breaches, hypotheticals that feel fake, or a lecture on “best practices.”

Rebecca Taylor (00:00)
Hello and welcome to this episode of HR Voices. I'm Rebecca Taylor, your host, and I'm joined today by Valerie Capers Workman. So excited to have Valerie here. Valerie's the CHRO of Empower Pharmacy and has a really cool background that I could probably spend this whole podcast just asking her about, but for the sake of keeping things a little bit more streamlined to the topic at hand. ⁓ Valerie, welcome. Thank you so much. And I'd love to get right into some of the questions if you're okay with that.

Valerie Capers Workmam (00:29)
I am so excited to be here. It's so cool to meet you. Let's go.

Rebecca Taylor (00:33)
All

right, all right. So I've done my LinkedIn stalking before this conversation, but for those who are listening who haven't done that, can you tell us about your role, about your company and the people that you're supporting?

Valerie Capers Workmam (00:44)
Yeah, sure. So I have the coolest job right now. I'm CHRO of Empower Pharmacy and we are a compound pharmacy that is all about helping people to live happier, healthier lives in a way that doesn't require them to choose between paying their rent and taking care of their health. And so it is all about affordability and really ensuring that they have the means to take care of things that are most critical to them, which is their personal well-being. ⁓ I am specifically charged with AI ⁓

both at the HR level and at the entire company level. I am an AI super fan ⁓ with understanding what all the issues and concerns are, but I've written two books on AI. I'm a fan of AI and so getting to build the HR tech stack with AI in mind to transform the way we do things to make them AI powered. And at the end of the day, it's all about helping people have happier, healthy lives. I could not have a better job right now.

Rebecca Taylor (01:41)
That's so cool. It's such a good connection of sort of your expertise, your interest in a purpose, right? Sometimes it's hard to find that intersection. So I get being just really, really motivated by the vision and the mission of the company too. I think it's so cool. So we talked very briefly about this before we started recording. ⁓ So you're leading AI transformation and you're leading it especially from the HR lens and the HR perspective. So what are some of the challenges that come with that and how are you kind of

Valerie Capers Workmam (01:54)
Me too.

Rebecca Taylor (02:09)
I wouldn't even say overcoming them, just addressing them, even if they're not overcome yet. Like, what makes that so hard for some companies?

Valerie Capers Workmam (02:16)
Yeah, and what's interesting, what makes it hard is, and I wrote a post on LinkedIn today, similar to the challenges that everybody's seeing, is there's a lot of fear around AI still. So the fear that it's going to replace people, the fear that you don't get to grow and truly develop because you're leaning on AI as a crutch, the fear that AI will replace decision-making, the fear that it's going to make decisions where people should be making them. So all of those things, and then the ethical considerations,

Rebecca Taylor (02:25)
Yeah.

Valerie Capers Workmam (02:46)
and the IP considerations and the security considerations. There's a lot to manage around before you can actually focus on doing the thing. But the biggest challenge is the fear, the security concerns, the safety concerns. At the end of the day, particularly for HR, how do we make people understand we're not trying to replace people? We're just trying to help everyone do their job faster, better, and be more effective. That's the biggest challenge right now.

Rebecca Taylor (02:56)
Yeah.

Yeah, so it's more in the perception of the people side of it than it is in the technology itself. Even though the technology itself has its own stuff, it's more the people part leaning into the tech, it sounds like.

Valerie Capers Workmam (03:24)
Exactly, you've got to manage for, ⁓ especially for companies or people like myself, HR leaders who believe you cannot be excellent without AI. And how do we make sure that people understand that while they also understand we're not trying to replace you? That's an easier said than done message, but it's really critical for us to overcome that perception. And then there's also the inequity piece where there's a perception that depending on where you graduated, depending on where you are in

your career, you're further down the road, you're more skilled, you're more AI fluent, and how do we level the playing field? there are a lot of ⁓ challenges, roadblocks that have to be overcome to get to where we're trying to go.

Rebecca Taylor (04:11)
I'm gonna ask what, I don't know, might be a controversial question or might not. Maybe it'll get cut, who knows? How much of the challenge do you think it is just people getting in their own way versus it being an actual challenge to overcome?

Valerie Capers Workmam (04:14)
Love controversy.

I love that it is controversial.

It's controversial because it's true. So the saying that I have adopted is, know, AI is not about replacing the person next to you. That is not the issue. And the mantra that everybody's been using is not correct. AI is about the willingness to accept change and allowing fear not to replace your ability to adapt. That's what AI is all about. So it really is that there's a lot of reluctance. There's, you know, I posted something yesterday

about AI is leveling the playing field in such a way that excellence is now redefined and that you cannot be excellent if you don't use AI. And I got a really kind of snarky comment. And I thought, is that controversial right now? Like, do I really have to convince people that you cannot be excellent any longer if you're not using AI? It's controversial. And so, yes, it's the reluctance and the fear ⁓ that's very much pervasive.

Rebecca Taylor (05:04)
Mm-hmm.

Yeah, I'm shocked. Snarky comments from people on social media.

Yes.

Valerie Capers Workmam (05:28)
of even even in 2026.

Rebecca Taylor (05:31)
get it sometimes, to be honest, someone does have a fear of losing their job, losing their role, think sometimes there isn't enough conversation about the good part and there's more conversation, at least not real conversation. Sometimes there's propaganda, sometimes there's marketing about the good part, But there isn't enough conversation about, I think, the bridge to get to that and that it's not easy and it's not supposed to be easy. That's what makes learning kind of,

sort of the foundation learning is always difficult learning something new. ⁓ But I think that's kind of the part that is so interesting about kind of where we are now is that I've always seen that, yes, there are real challenges, right? But I find that sometimes it is a lot of folks kind of getting in their own way in that sense. ⁓

Valerie Capers Workmam (06:16)
Yeah.

Yeah,

and also the perception that AI is cheating in some way. I had a moment, I know I'm going to be using this in Keynotes for like the next year. I was talking to somebody on my team and the person delivered something and it was okay. And I said, here's what I need you to do. I need you to put it in the chat and I need you to ask these three questions and I need you to bring it back to me. And the person brought it back to me two times where I could tell that person had not done that. And I says, okay, here's what I need you to do. I need you to do this.

Rebecca Taylor (06:21)
Mm-hmm.

He

Valerie Capers Workmam (06:48)
put it in chat, get the responses and then come back to me. The person said, well, can I get it back to you tomorrow? I said, no, I want it in 15 minutes. The person delivered it back. It was outstanding.

Rebecca Taylor (06:54)
Yeah, yeah.

Valerie Capers Workmam (06:59)
And what was unusual is you would think that the person would be thrilled that I said what they did was outstanding and they were disappointed. And it was almost as if they felt they were getting complimented for work they didn't do or complimented for because they couldn't get it done. And yet what I was applauding was how exceptional that piece of work was when we had worked together, when that person worked with AI, because now we can move on to like five other things. But when I saw that sort of that disappointment

Rebecca Taylor (07:19)
Right?

Yeah.

Valerie Capers Workmam (07:29)
and it almost shame I thought what have we done where we are convincing people that AI uses is cheating especially at the undergraduate level where you're not supposed to use it but then the day you graduate supposed to use it and I thought we've got a long way to go to make everybody comfortable that it's not a cheat it's really a way of excelling so you can focus on the matters that really require strategic thinking we have a long way to go

Rebecca Taylor (07:33)
Mmm.

Yeah.

Yeah.

Yeah,

yeah. I wonder if it's also disappointment and maybe disappointment that's rooted in fear because it's like, well, if that's really easy to do and that normally takes me this much time, why would they still pay me to do this job? It's almost like it requires this rethinking and re-understanding of how we work because it's it's okay for something to be easy now. I I was a headhunter for a long time and some of the folks who were there who were training me had been...

Valerie Capers Workmam (08:14)
Yeah.

Rebecca Taylor (08:22)
doing this since like the 70s and they were like, we used to have to hire a courier who would run resumes to customers and you now, and you would have two or three interviews in a day. Now we email, you know, 10s and 20 resumes a day and it doesn't make us any less efficient, but it just changes the sort of speed and accuracy even though we still do the job, it's just done a little bit differently.

Valerie Capers Workmam (08:42)
Exactly. And as a follow up to that story, because today, because we had gotten through that part so quickly, this same person asked me a question about a strategic game plan that we are working on. And this person said, can I ask you a question? Should we really be doing X? It was such a great question. I had to convene a small working group. Then we had to thought process it. And then we thought about it for half an hour. And then we changed some of the things we were doing. We would not have been able to have that conversation

if the person was still working on the basics and this is the same person. So I know today this person is feeling great because I said, thank you for challenging me on that. If you hadn't asked me that question, we wouldn't have gotten to this place. they will people will get there if they have the right leaders focusing on use it for the small task. But when you have the heavy, tough, strategic EQ thought process, you need to leave more space for that. I know this person now gets why that that person is

that small project was done because we have to do some really deep thinking today. You don't always get the benefit of that lesson happening so quickly, you know, on the 24 hours, but it's important to know that that's where we're trying to get people to go. Focus on task-oriented AI work so you can be strategic.

Rebecca Taylor (09:49)
Yeah. Yeah. ⁓

Yeah, I love that. Cause I think there's also this sort of expectation or assumption that something has to be perfect too. So sometimes you'll see, you know, and I, and I still overcome this, right? Like I'm not, I'm certainly not perfect in my age, in AI journey in any way. ⁓ but sometimes it can feel like you're relinquishing control or it's, you know, sometimes workflow automations are great.

Valerie Capers Workmam (10:19)
Yeah. Yeah.

Rebecca Taylor (10:24)
Sometimes there's a change in the product that all of sudden automates something that puts a message out there that shouldn't have been automated and then you have to kind of backpedal. So there is sort of that, I think there's a lot of stress of just like, well, what if it takes my inbox hostage and starts doing all these things, right? And that's where in my experience, especially in HR is where people kind of get really hung up because they're like, what if AI accidentally declines a candidate that it shouldn't or if it takes an action that it shouldn't.

Valerie Capers Workmam (10:31)
Yeah. Yeah.

you

Yeah. Yeah.

Yeah.

Rebecca Taylor (10:53)
And I think

it's going to happen as the technology evolves accidentally. And I think it's almost as important to understand how to address those mess ups and for the market to understand that they're gonna happen more so than trying to not let them happen, right? Like we all get typos every once in a while. What's the equivalent of the typo that we can all say, that's probably just that. And we kind of just figure it out.

Valerie Capers Workmam (11:12)
Yeah.

But I think you can solve that by design. know, when we're rebuilding our entire HR tech stack, everything, performance management, ⁓ learning and development, compensation planning, know, everything is going to be AI fueled by state of the art platforms. But in all of our designs, when we're talking to vendors, I'm being very clear, my team is being very clear, we are the last mile. The humans are the last mile decision makers, and we're not interested in any system that you want to pitch to us that

Rebecca Taylor (11:26)
Mmm.

Valerie Capers Workmam (11:48)
removes the human equation from the last mile because that's where our expertise comes from strategy comes from EQ comes from empathy comes from so it all is how you design your program and if you design it so that any result or any action cannot be taken without a human leading that I think you'll circumvent 99.9 percent of those issues where an AI is going to make a mistake because it can't think AI does not think people really need

Rebecca Taylor (12:16)
Right? Right.

Valerie Capers Workmam (12:18)
all it is is a string of words together that make a lot of sense and the more words you put into your prompt the better the response is but it's not thinking. Only humans can think and I think that's if we remember that that last mile has to be human we'll be fine.

Rebecca Taylor (12:29)
Right.

Yeah, I think it's a great way to put it. That last mile has to be human. So it gets you so far and then you sort of have to take it the rest of the way. I think that's one of the things that, you before I joined All Voices, I co-founded an AI performance management company. And so I've been in the AI space for a while. And the thing that really kind of got me interested in working with All Voices is because they're covering the employee relations side with AI tools. And coming from HR, I've done my fair share of investigations. I remember.

Valerie Capers Workmam (12:42)
Exactly.

Mmm.

Thank

Rebecca Taylor (13:05)
If you're lucky, you're using maybe a spreadsheet, maybe a Google form. I had one of my horror stories, as I remember, at one of my old companies, a manager was documenting everything in a notebook and then left that notebook in the communal kitchen by accident, which was then found, you know, one of those. And so one of the things I asked the team is I was like, well, employee relations is one of the more sensitive areas, obviously, for AI. So how does this work?

Valerie Capers Workmam (13:18)
⁓ of course, of course, of course, of course, of course.

Rebecca Taylor (13:32)
There is sort of that, the reason that I was like, okay, I can understand how this is sort of a good thing is that there is that last mile kind of piece of it. And it just helps you make sense of the data. So, you know, is this something that I need to take action on? Or is this something that I'm kind of just, you know, tracking themes and trends and maybe a less charged kind of way. So it's like, I think being able to use those tools in that way can be really, really beneficial. But again, if it's so automated that...

Valerie Capers Workmam (13:40)
Yeah.

Rebecca Taylor (13:59)
All Voices is determining who's working at your company or not. Like you can't, it's never going to do that because that can never be the way that these tools work.

Valerie Capers Workmam (14:03)
Yeah.

Exactly, AI can't have a compassionate conversation with someone who feels like they're being mistreated. You know, it can't hold someone's hand who had a medical emergency and they're trying to figure out, you know, how do they handle the benefits? You know, it can't coach someone through, this is a feedback session that you've had and you took it the wrong way and let me tell you what I did, you know, when I was in your position. It can't do those things. However, the systematic way of inputting data so that if there's a problematic

Rebecca Taylor (14:12)
Yeah.

Yeah.

Valerie Capers Workmam (14:36)
who keeps popping up. know, if employees keep stumbling over that same, don't understand how to access this benefit. It can teach the HR team how to solve for those issues, how to identify those problems, and then how to predict and avoid future problems because you have that aggregation of data. So it's irreplaceable in its ability to help us be better at what we do, but it can't be great at what we do. It can't be great at what we do, and that's being key.

Rebecca Taylor (14:38)
Mm-hmm

Yes.

Valerie Capers Workmam (15:06)
and bringing that human to human resources, which I like human resources. I prefer it over people because it is all about humanity right now and it can't do what we do. But we're better when we use it. That's the key.

Rebecca Taylor (15:10)
Me too.

Yeah.

Ooh,

that is the clip. That is the clip for this. Cause like, I'm just like, yes, yes, let's go. I completely agree. And so I know I have one kind of question as we kind of wrap up towards the end of this, but so you're revamping your HR tech stack or your AI strategy in general. So can you tell us about an experiment that you've, that you're really excited about something that you either did or an experiment that you're starting that maybe someone who's listening might want to kind of explore and try themselves too.

Valerie Capers Workmam (15:45)
Yeah, what we're working on ⁓ right now is one of my goals is to make sure that the company is AI fluent ⁓ and defining what AI fluent means. And for us, AI fluency means you understand exactly how to use AI in your particular role to do that thing better. And so we are testing our curriculum right now. ⁓ HR, Talonic, and a few of the other operational folks are in that team. And we have ⁓ one of our directors leading that program.

So we are one of the very early adopters of putting together a company wide curriculum on utilizing AI. And so we're so excited that the way we're doing it is we're taking a small group first. I'm going to put them, put everyone through their paces and see how it feels to be coached that way. And then we're going to expand it to company wide. So like many companies, I can't give you the outcome. Like talk to me next year this time. And I'll tell you how great it was when we launched it and what mistakes we made. But the thing is we're doing it. That's what's

most important. We're talking, you can't tell people you have to use AI and your performance has to be better with AI and then you don't teach them how to use AI. So we are walking the walk as we're talking the talk. So I would say our first pilot program we're working on that right now. We have the small team. I'm so excited that the excitement in the company and the way people are, because one of my personal mantras is ensuring that no one gets left behind in the age of AI. That's why I wrote my book, by the way, Quantum Regression, the Art Science of Pure Romance.

Rebecca Taylor (17:13)
Yeah, ⁓ have it in my notebook

Valerie Capers Workmam (17:15)
Thank you. It's the new version,

Rebecca Taylor (17:15)
or I have it in my thing to look at, yeah.

Valerie Capers Workmam (17:18)
2026, not the 2023 version, because I'm on my second edition. the fact that AI can level the playing field, but only if everybody has access to the same tools at the same time. And so the only way to ensure that is you have to roll out a company-wide mandatory training so that people don't suddenly get further behind inadvertently because of AI. That's the outcome you don't want.

Rebecca Taylor (17:30)
Yes.

Valerie Capers Workmam (17:45)
would say just go ahead and launch something. Start a pilot program. Get a few brave souls who want to figure out a way that it will work for the company and just get started. Just get started.

Rebecca Taylor (17:57)
I love that. Momentum beats perfection any day. It's like, something is better than nothing. That's always my other thing too. ⁓ That is great. And that's such a great takeaway. I think that that was like, I think that that's a really good kind of thing that we're gonna be finding in a lot of these kinds of themes and conversations on this show is like the, just the concept of just start something. doesn't have to be perfect. It's almost like shed the concept of perfection because if you try to learn something,

Valerie Capers Workmam (17:59)
Every time. Every time. I agree. I agree.

Exactly.

Rebecca Taylor (18:25)
perfectly, this technology changes so quickly that by the time you learn it to the point where you feel like you're an expert in it, guess what? You're already behind on the next thing. So just keep going. ⁓

Valerie Capers Workmam (18:33)
Exactly, exactly. And there's nothing

better than failing. Failing is the best precursor to success. And when you put in prompts and you get horrible answers, there's nothing better than that. Because number one, it reminds you you're smarter than the machine. And number two, it reminds you that you continue to refine how you ask questions, how you think, how you address problems by failing. That's the way to truly succeed. It's so cliche. It is so true. So true.

Rebecca Taylor (18:46)
Yeah.

It's true,

and failure can be funny. Some of my best AI learns that have been just from generating an image that I'm like, well, that's not what I was looking for at all. It's just...

Valerie Capers Workmam (19:03)
Okay.

you should

hear me. I have four chests that I love. You should see me interacting with them. Sometimes like, are you serious right now? Like, what did you just tell me right now? That was ridiculous.

Rebecca Taylor (19:15)
Yes, I do the same. I do the same thing. I talk to... I do the same thing.

I'm like, I'm sorry. Did you ingest something before we had this conversation? And then I'm like, I know it's a robot, but still. ⁓ I love this. Well, Valerie, thank you so much for coming onto HR Voices. I love this conversation. I know that I can talk to you for years probably. So I'm really glad that we're in touch. And thank you everybody for listening and have a great rest of your day.

Valerie Capers Workmam (19:24)
It's too funny.

Thank you so much for having me, Rebecca. Take care.

Rebecca Taylor (19:45)
You too.